Multi-scale traffic performance modeling of transportation systems subjected to multiple hazards
Date
2019
Authors
Hou, Guangyang, author
Chen, Suren, advisor
van de Lindt, John, committee member
Atadero, Rebecca, committee member
Trumbo, Craig, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
Transportation systems are very vulnerable to natural or manmade hazards, such as earthquakes, floods, hurricanes, tsunamis, terrorism, etc. In the past years, extreme hazards have caused significant physical and functional damages to transportation systems around the world. Disruption of transportation systems by multiple hazards will impede social and commercial activities, and hamper the post-disaster emergency response and long-term recovery of the damaged community. The main purpose of this dissertation is to develop advanced performance assessment techniques of transportation systems subjected to multiple hazards in the link level and network level. It is expected that the developed techniques in this dissertation will help stakeholders to make risk-informed decisions in terms of effective prevention and preparation measures to enhance and facilitate resilience of transportation systems. A suite of simulation methodologies are developed to evaluate the performance of critical transportation components (e.g. bridges and road segments) and transportation networks subjected to multiple hazards in this dissertation. Firstly, an advanced traffic flow simulation framework is developed to predict the post-hazard performance of a typical highway system under hazardous conditions. Secondly, a simulation methodology is developed to study the traffic performance of degraded road links being partially blocked following extreme events. Thirdly, a new approach is proposed to develop travel time functions of partially blocked roads in urban areas through microscopic traffic simulation. Fourthly, an integrated model is developed to assess single-vehicle traffic safety performance of stochastic traffic flow under hazardous driving conditions. Finally, an integrated probabilistic methodology is developed to model the performance of disrupted infrastructures due to fallen urban trees subjected to extreme winds.